Document-AI / OCR Extraction Pipeline

About this Gig

You get a pipeline that turns messy files into clean, structured, queryable data. Invoices, contracts, forms, scanned PDFs, and images go in, and structured JSON or database rows come out, with the fields you actually care about extracted and validated. I combine OCR, layout-aware parsing, and LLM extraction so it handles real-world documents, not just clean templates. I add confidence scoring and validation rules so low-quality extractions get flagged for review instead of silently passing. You get a FastAPI service or batch job, a defined output schema, and accuracy measured on your own document samples. This builds on the document-AI and ingestion work behind my production RAG systems, including SharePoint ingestion for a large South African bank and a 600k+ document knowledge base. This is a scoped, milestone-based engagement that starts with a short discovery call, with the final timeline confirmed after scoping. For a document-AI or OCR pipeline that is typically around 4 to 6 weeks.

Requirements

A set of sample documents that represent the range you deal with, the exact fields you want extracted, your target output format (JSON, CSV, database), expected volume, and any accuracy or compliance requirements. A short call to confirm the schema helps.

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